1 to 25 of 81 Remote Amazon Redshift Jobs in the UK

Amazon Web Services is the market leader and technology forerunner in the Cloud business. As a member of the AWS Support team you will be at the forefront of this transformational technology, assisting a global list of companies and developers that are taking advantage of a growing set of … practices for applications, servers and networks? Do you want to be part of a customer facing technology team helping to ensure the success of Amazon Web Services (AWS) as a leading technology organization? If you fit the description, you might be the person we are looking for! We are … breaking technologies. Apply advanced troubleshooting techniques to provide unique solutions to our customers' individual needs. Interact with leading engineers around the world. Partner with Amazon Web Services teams to help reproduce and resolve customer issues. Leverage your extensive customer support experience to provide feedback to internal AWS teams on More ❯

Engineering with AWS. Strong skills in Python or Scala and experience with SQL databases . Hands-on experience with AWS services (S3, Lambda, Glue, Redshift, Athena, etc.). Knowledge of data modelling, pipeline orchestration (Airflow) , and cloud infrastructure (IaC – Terraform, CloudFormation). Experience working in financial services or FinTech More ❯

throughput, scalable, resilient and secure data pipelines. Experience with the following AWS technologies: Glue jobs, Athena, S3, Step functions, Lambda, RDS (Aurora Postgres), DMS, Redshift, QuickSight, Kinesis Firehose. Expert knowledge of SQL. Hands-on experience with Kafka. Hands-on experience with Terraform. Hands-on experience of Python with a More ❯

Experience working with a modern data analytics stack. Excellent communication and stakeholder management skills. Nice to have Familiarity with the AWS environment (S3, Athena, Redshift). Experience with Python (Airflow, dbt, PySpark, Pandas). Experience with Snowflake. Experience with Thoughtspot. Familiarity with the command line. Some understanding of Kafka. More ❯

workflows. Strong analytic skills related to working with unstructured datasets. Engineering best practices and standards. Experience with data warehouse software (e.g. Snowflake, Google BigQuery, Amazon Redshift). Experience with data tools: Hadoop, Spark, Kafka, etc. Code versioning (Github integration and automation). Experience with scripting languages such as More ❯

data analysis, machine learning, and data visualization. In-depth knowledge of cloud platforms (AWS, Azure, Google Cloud) and related data services (e.g., S3, BigQuery, Redshift, Data Lakes). Expertise in SQL for querying large datasets and optimizing performance. Experience working with big data technologies such as Hadoop, Apache Spark More ❯

data analysis, machine learning, and data visualization. In-depth knowledge of cloud platforms (AWS, Azure, Google Cloud) and related data services (e.g., S3, BigQuery, Redshift, Data Lakes). Expertise in SQL for querying large datasets and optimizing performance. Experience working with big data technologies such as Hadoop, Apache Spark More ❯

in building data virtualisation layers and data semantic layers. Strong knowledge of relational databases (MySQL, PostgreSQL), experience with data warehousing concepts and tools (Snowflake, Redshift), data lakes and data lakehouses. Familiarity with distributed computing frameworks like Apache Hadoop, Apache Spark, and NoSQL databases (such as MongoDB, Cassandra). An More ❯

and optimise Kafka clusters for real-time data streaming. Oversee and maintain containerized workloads using EKS (Kubernetes on AWS) . Support data infrastructure, including Amazon Redshift for analytics and storage. Implement security best practices and compliance controls within cloud environments. Collaborate with development, security, and operations teams to … such as Sentry and Grafana). Design procedures for system troubleshooting and maintenance. Required Skills & Experience Strong experience with AWS services , particularly EKS, Kafka, Redshift, and CloudWatch . Hands-on experience with Kubernetes and container orchestration. Experience with CI/CD tools (Jenkins, GitHub Actions, GitLab CI, or similar More ❯

Strong analytic skills related to working with unstructured datasets. Engineering best practices and standards. Desirable Experience with data warehouse software (e.g., Snowflake, Google BigQuery, Amazon Redshift). Experience building and optimizing pipelines and ETL/ELT workflows. Working knowledge of data warehouse technologies (Snowflake, BigQuery). Code versioning More ❯

. Strong analytic skills related to working with unstructured datasets. Engineering best practices and standards. Experience with data warehouse software (e.g. Snowflake, Google BigQuery, Amazon Redshift). Experience building and optimising pipelines and ETL/ELT workflows. Working knowledge of data warehouse technologies (Snowflake, BigQuery). Code versioning More ❯

skills in Python and SQL to develop and optimise data models and processes. Experience with data management platforms such as Snowflake, BigQuery, MongoDB, DynamoDB, Redshift, and PostgreSQL will be crucial. Blockchain Solutions Engineering: Apply knowledge from previous engagements where blockchain technology, particularly in data handling and staking mechanisms, was More ❯

not? We’ll help you get there: Understanding of cloud computing security concepts Experience in relational cloud-based database technologies like Snowflake, BigQuery or Redshift Experience in open-source technologies like Spark, Kafka, Beam understanding of Cloud tools such as AWS, Microsoft Azure or Google Cloud Familiarity with DBT More ❯

in SQL, PL/SQL, and database management systems such as Oracle, SQL Server, MySQL, and PostgreSQL. Experience with data warehousing tools like Snowflake, Redshift, or BigQuery. Analytical Skills : Strong analytical and problem-solving skills, with the ability to analyse complex data requirements and develop effective solutions. Communication Skills More ❯

and proficient in designing and implementing scalable data architectures Strong experience with ETL processes, data modelling, and data warehousing (we use airflow, dbt and redshift) Expertise in database technologies, both relational (SQL) and NoSQL Knowledge of cloud platforms (AWS) Solid understanding of data security measures and compliance standards Excellent More ❯

how these can be practically applied. Experience with Python or other scripting languages. Good working knowledge of the AWS data management stack (RDS, S3, Redshift, Athena, Glue, QuickSight) or Google data management stack (Cloud Storage, Airflow, Big Query, DataPlex, Looker). About Our Process We can be flexible with More ❯

Scala, Spark, and SQL. Expertise in either AWS or Azure cloud platforms, with hands-on experience in key services such as: AWS: EMR, Glue, Redshift, Kinesis, Lambda, DynamoDB Azure: Data Factory, Synapse, Databricks, Event Hubs, Logic Apps, Cosmos DB Understanding of best practices for end-to-end software development More ❯

to-end data platforms that are scalable, secure, and cost-effective using cloud technologies (AWS, GCP, Azure). Implement hybrid cloud architectures (e.g., Snowflake, Redshift, BigQuery), and migrate legacy systems to modern cloud-based platforms. Lead the creation of Proofs of Concept (PoCs) and Minimum Viable Products (MVPs) for More ❯

ETL processes and database management systems (e.g., MySQL, PostgreSQL, MongoDB) Hands-on experience with AWS services for data processing, storage and analysis (e.g., S3, Redshift, EMR, Glue) Familiarity with programming languages such as Python or Java Understanding of data warehousing concepts and data modeling techniques Experience working with big More ❯

processes and database management systems (e.g., MySQL, PostgreSQL, MongoDB). Hands-on experience with AWS services for data processing, storage and analysis (e.g., S3, Redshift, EMR, Glue). Familiarity with programming languages such as Python or Java. Understanding of data warehousing concepts and data modeling techniques. Experience working with More ❯

Technical Skills: Languages: Python, SQL, R. Big Data: Apache Spark, Hadoop, Kafka, or similar. Timeseries Database: InfluxDB or TimescaleDB, or similar. Cloud Platforms: AWS Redshift, Azure Synapse, or similar. ML/AI Tools: scikit-learn, TensorFlow, PyTorch. Data Visualization: Power BI, Tableau, or similar. Version Control: Git. Preferred Qualifications More ❯

and proficient in designing and implementing scalable data architectures. Strong experience with ETL processes, data modelling, and data warehousing (we use Airflow, dbt, and Redshift). Expertise in database technologies, both relational (SQL) and NoSQL. Expert in cloud platforms (AWS). Solid understanding of data security measures and compliance More ❯

data challenges in a fast-paced environment. Have a solid understanding of data warehousing concepts and familiarity with cloud platforms like BigQuery, Snowflake, or Redshift . Are proactive in improving data processes, documentation, and analytics best practices. (Bonus) Exposure to Python for data analysis is a plus! Our benefits More ❯

solutions to automate data ingestion, transformation, and orchestration across systems. Own data operations infrastructure: Manage and optimise key data infrastructure components within AWS, including Amazon Redshift, Apache Airflow for workflow orchestration and other analytical tools. You will be responsible for ensuring the performance, reliability, and scalability of these More ❯

projects, including planning, execution, and monitoring Experience Hands-on expertise with data warehousing and management, including data processing, integration, and advanced analytics (e.g., Snowflake, Amazon Redshift, Databricks, Cloudera, Oracle). Experience managing a portfolio of technical programmes within an established Enterprise Data office/management function. Technical understanding More ❯